Native: Add MCP implementation

Author: sudeeptarlekar

application/apps/indexer/Cargo.toml

@@ -14,6 +14,7 @@ members = [
     "addons/text_grep",
     "addons/bufread",
     "indexer_base",
+    "mcp",
     "merging",
     "parsers",
     "plugins_host",

application/apps/indexer/mcp/Cargo.toml

@@ -0,0 +1,34 @@
+[package]
+name = "mcp"
+edition.workspace = true
+version.workspace = true
+authors.workspace = true
+
+[dependencies]
+axum = { version = "0.7", features = ["macros"] }
+ollama-rs = { version = "0.3", features = ["stream"] }
+rmcp = { version = "0.11", features = [
+  "client",
+  "macros",
+  "reqwest",
+  "schemars",
+  "server",
+  "transport-io",
+  "transport-streamable-http-client-reqwest",
+  "transport-streamable-http-server",
+  "transport-streamable-http-server-session",
+] }
+anyhow.workspace = true
+log.workspace = true
+reqwest = { version = "0.12.25", features = ["json"] }
+schemars = "1.1"
+serde_json.workspace = true
+serde.workspace = true
+thiserror.workspace = true
+tokio-util.workspace = true
+tokio.workspace = true
+rand = "0.9"
+url = { version = "2.5", features = ["serde"] }
+
+[lints]
+workspace = true

application/apps/indexer/mcp/src/agents/mod.rs

@@ -0,0 +1,36 @@
+use ollama_rs::generation::chat::{ChatMessage, ChatMessageResponse};
+use rmcp::model::ListToolsResult;
+use serde::{Deserialize, Serialize};
+
+use crate::errors::McpError;
+
+// pub mod claude;
+pub mod ollama;
+pub mod open_ai;
+
+pub const LLM_API_KEY: &str = "LLM_KEY";
+
+pub trait LlmAgent {
+    fn new(model: &str, url: &str) -> Self;
+
+    async fn send_chat_message(
+        &self,
+        prompt: String,
+        history: &mut Vec<ChatMessage>,
+        tools: ListToolsResult,
+    ) -> Result<ChatMessageResponse, McpError>;
+
+    fn api_key() -> Option<String> {
+        std::env::var(LLM_API_KEY).ok()
+    }
+}
+
+pub trait ChatResponse {}
+
+#[derive(Debug, Default, Serialize, Deserialize)]
+pub enum LlmProvider {
+    #[default]
+    Ollama,
+    OpenAI,
+    Claude,
+}

application/apps/indexer/mcp/src/agents/ollama.rs

@@ -0,0 +1,80 @@
+use ollama_rs::generation::{
+    chat::{ChatMessage, ChatMessageResponse, request::ChatMessageRequest},
+    tools::{ToolFunctionInfo, ToolInfo, ToolType},
+};
+use rmcp::model::ListToolsResult;
+use serde::{Deserialize, Serialize};
+use serde_json::Value;
+use url::Url;
+
+use super::LlmAgent;
+use crate::{agents, errors::McpError};
+
+#[derive(Debug, Clone, Deserialize, Serialize)]
+pub struct Ollama {
+    pub model: String,
+    pub url: String,
+    pub api_key: Option<String>,
+}
+
+impl Default for Ollama {
+    fn default() -> Self {
+        Self {
+            model: String::from("llama3.2"),
+            url: String::from("http://localhost:11434"),
+            api_key: None,
+        }
+    }
+}
+
+impl LlmAgent for Ollama {
+    fn new(model: &str, url: &str) -> Self {
+        Self {
+            model: String::from(model),
+            url: String::from(url),
+            api_key: None,
+        }
+    }
+
+    async fn send_chat_message(
+        &self,
+        prompt: String,
+        history: &mut Vec<ChatMessage>,
+        tools: ListToolsResult,
+    ) -> Result<ChatMessageResponse, McpError> {
+        let url = Url::parse(self.url.as_str()).map_err(|err| McpError::Generic {
+            message: format!("Error while parsing URL for the Ollama Agent; {err:?}"),
+        })?;
+
+        let client = ollama_rs::Ollama::from_url(url);
+
+        let mcp_tools = tools
+            .tools
+            .iter()
+            .map(|tool| ToolInfo {
+                tool_type: ToolType::Function,
+                function: ToolFunctionInfo {
+                    name: tool.name.to_string(),
+                    description: tool
+                        .description
+                        .as_ref()
+                        .map(|x| x.to_string())
+                        .unwrap_or("No description".to_string()),
+                    parameters: serde_json::from_value(Value::Object((*tool.input_schema).clone()))
+                        .unwrap_or(schemars::json_schema!({"type": ["object", "null"]})),
+                },
+            })
+            .collect::<Vec<ToolInfo>>();
+
+        let chat_message_request =
+            ChatMessageRequest::new(self.model.clone(), vec![ChatMessage::user(prompt)])
+                .tools(mcp_tools);
+
+        client
+            .send_chat_messages_with_history(history, chat_message_request)
+            .await
+            .map_err(|e| McpError::Generic {
+                message: e.to_string(),
+            })
+    }
+}